Presenting “Malware Classifier” Tool

Karthik here from Adobe PSIRT. Part of what we do at PSIRT is respond to security incidents. Sometimes this involves analyzing malware. To make life easier, I wrote a Python tool for quick malware triage for our team. I’ve since decided to make this tool, called “Adobe Malware Classifier,” available to other first responders (malware analysts, IT admins and security researchers of any stripe) as an open-source tool, since you might find it equally helpful.

Malware Classifier uses machine learning algorithms to classify Win32 binaries – EXEs and DLLs – into three classes: 0 for “clean,” 1 for “malicious,” or “UNKNOWN.” The tool extracts seven key features from a binary, feeds them to one or all of the four classifiers, and presents its classification results.

The tool was developed using models resultant from running the J48, J48 Graft, PART, and Ridor machine-learning algorithms on a data set of approximately 100,000 malicious programs and 16,000 clean programs.

I will be speaking about the research behind the tool at Infosec Southwest 2012 in Austin, TX, on April 1. If you’re going to be there, I look forward to meeting up and discussing product security and secure engineering at Adobe.